Measurement of retina vessels by segmentation of images reconstructed from optical coherence tomography data

• Autorzy: Marciniak Tomasz , Stankiewicz Agnieszka , Dąbrowski Adam , Stopa Marcin , Rakowicz Piotr , Marciniak Elżbieta

Identyfikatory

DOI

10.24425/mms.2019.129581

• Języki publikacji: EN

Abstrakty

EN

In this paper methods and their examination results for automatic segmentation and parameterization of vessels based on spectral domain optical coherence tomography (SD-OCT) of the retina are presented. We present three strategies for morphologic image processing of a fundus image reconstructed from OCT scans. A specificity of initial image processing for fundus reconstruction is analysed. Then, the parameterization step is performed based on the vessels segmented with the proposed algorithm. The influence of various methods on the vessel segmentation and fully automatic vessel measurement is analysed. Experiments were carried out with a set of 3D OCT scans obtained from 24 eyes (12 healthy volunteers) with the use of an Avanti RTvue OCT device. The results of automatic vessel segmentation were numerically compared with those prepared manually by the medical doctor experts.

Słowa kluczowe

EN

optical coherence tomography; image processing; mathematical morphology; vessel segmentation

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2019
• Tom: Vol. 26, nr 3
• Strony: 449--461
• Opis fizyczny: Bibliogr. 27 poz., rys., tab., wykr., wzory

Twórcy

autor

Marciniak Tomasz

• Poznań University of Technology, Institute of Automation and Robotics, Piotrowo 3a, 60-965 Poznań, Poland

autor

Stankiewicz Agnieszka

• Poznań University of Technology, Institute of Automation and Robotics, Piotrowo 3a, 60-965 Poznań, Poland

autor

Dąbrowski Adam

• Poznań University of Technology, Institute of Automation and Robotics, Piotrowo 3a, 60-965 Poznań, Poland

autor

Stopa Marcin

• Poznań University of Medical Sciences, Chair of Ophthalmology and Optometry, Rokietnicka 5D, 60-806 Poznań, Poland
• Poznań University of Medical Sciences, Clinical Eye Unit and Pediatric Ophthalmology Service, Heliodor Święcicki Medical Hospital, Grunwaldzka 16/18, 60-780 Poznań, Poland

autor

Rakowicz Piotr

• Poznań University of Medical Sciences, Chair of Ophthalmology and Optometry, Rokietnicka 5D, 60-806 Poznań, Poland
• Poznań University of Medical Sciences, Clinical Eye Unit and Pediatric Ophthalmology Service, Heliodor Święcicki Medical Hospital, Grunwaldzka 16/18, 60-780 Poznań, Poland

autor

Marciniak Elżbieta

• Poznań University of Medical Sciences, Chair of Ophthalmology and Optometry, Rokietnicka 5D, 60-806 Poznań, Poland
• Poznań University of Medical Sciences, Clinical Eye Unit and Pediatric Ophthalmology Service, Heliodor Święcicki Medical Hospital, Grunwaldzka 16/18, 60-780 Poznań, Poland

Bibliografia

• [1] Gardner, G.G., Keating, D., Williamson, T.H., Elliott, T.H. (1996). Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool. British Journal Ophthalmology, 80(11), 940-944.
• [2] Hart, W.E., Goldbaum, M., Cote, B., Kube, P., Nelson, M.R. (1997). Automated measurement of retinal vascular tortuosity. Proc. AMIA Fall Conference, 459-463.
• [3] Cheung, C.Y., Ikram, M.K., Sabanayagam, C., Wong, T.Y. (2012). Retinal microvasculature as a model to study the manifastations of hypertansion. Hypertension, 60, 1094-1103.
• [4] Li, L.J., Ikram, M.K., Wong, M.K. (2015). Retinal vascular imaging in early life: insights into processes and risk of cardiovascular disease. The Journal Physiology, 594(8), 2175-2203.
• [5] Honale, S.S., Kapse, S.S. (2012). A Review of Methods for Blood Vessels Segmentation in RetinalImages. International Journal Engineering Research & Technology (IJERT), 1(10), 1-6.
• [6] Webb, R.H., Hughes, G.W. (1981). Scanning Laser Ophthalmoscope. IEEE Transactions Biomedical Engineering, BME-28(7), 488-492.
• [7] Xu, J., Ishikawa, H., Wollstein, G., Schuman, J.S. (2008). Retinal vessel segmentation on SLO image. Proc. 30th Annu Int Conf IEEE Eng Med Biol Soc, 2258-2261.
• [8] Stankiewicz, A., Marciniak, T., Dabrowski, A., Stopa, M., Marciniak, E. (2014). A new OCT-based method to generate virtual maps of vitreomacular interface pathologies. Proc. 18th IEEE International Conference Signal Processing Algorithms, Architectures, Arrangements, Applications (SPA 2014), 83-88.
• [9] Heneghan, C., Flynn, J., O’Keefe, M., Cahill, M. (2002). Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysis. Medical Image Analysis, 6(4), 407-429.
• [10] Wong, T.Y., Knudtson, M.D., Klein, R., Klein, B.E.K., Meuer, S.M., Hubbard, L.D. (2004). Computer-assisted measurement of reitnal vessel diameters in the Beaver Dam Eye Study: methodology, correlation between eyes, and effect of refractive errors. Ophthalmology, 111(6), 1183-1190.
• [11] Kandasamy, Y., Smith, R., Wright, I.M., Hartley, L. (2012). Relationship between birth weight andretinal microvasculature in newborn infants. Journal Perinatology, 32, 443-447.
• [12] Fraz, M.M., Basit, A., Barman, S.A. (2013). Application of Morphological Bit Planes in Retinal Blood Vessel Extraction. Journal Digital Imaging, 26, 274-286.
• [13] El Abbadi, N.K., Al Saadi, E.H. (2013). Blood Vessels Extraction Using Mathematical Morphology. Journal Computer Science, 9(10), 1389-1395.
• [14] Mudassar, A.A., Butt, S. (2013). Extraction of Blood Vessels in Retinal Images Using Four Different Techniques. Journal Medical Engineering, 408120.
• [15] Maggioni, M., Katkovnik, V., Egiazarian, K., Foi, A. (2013). A Nonlocal Transform Domain Filter for Volumetric Data Denoising and Reconstruction. IEEE Trans Image Process, 22(1), 119-133.
• [16] Campbell, J.P., Zhang, M., Hwang, T.S., Bailey, S.T., Wilson, D.J., et al. (2017). Detailed Vascular Anatomy of the Human Retina by Projection-Resolved Optical Coherence Tomography Angiography. Scientific Reports, 7(42201).
• [17] Stankiewicz, A., Marciniak, T., Dąbrowski, A., Stopa, P., Rakowicz, M., Marciniak, E. (2015). Improving segmentation of 3D retina layers based on graph theory approach for low quality OCT images. Metrol. Meas. Syst., 23(2), 269-280.
• [18] Xu, J., Tolliver, D.A., Ishikawa, H., Wollstein, G., Schuman, J.S. (2009). 3D OCT retinal vessel segmentation based on boosting learning. In: Dössel O, and Schlegel WC, editors. Proc. World Congr Medical Physics Biomedical Engineering, IFMBE, Munich, Germany, 179-182.
• [19] Niemeijer, M., Garvin, M.K., Ginneken, B. van, Sonka, M., Abramoff, M.D. (2008). Vessel segmentation in 3D spectral OCT scans of the retina. Proc. SPIE Medical Imaging 2008 Image Processing, 69141R1-69141R8.
• [20] Niemeijer, M., Sonka, M., Garvin, M.K., Ginneken, B. van, Abramoff, M.D. (2008). Automated Segmentation of the Retinal Vasculature in 3D Optical Coherence Tomography Images. Investigative Ophthalmology & Visual Science, 49, 1832.
• [21] Hu, Z., Niemeijer, M., Abramoff, M.D., Garvin, M.K. (2012). Multimodal Retinal Vessel Segmentation From Spectral-Domain Optical Coherence Tomography and Fundus Photography. IEEE Transactions Medical Imaging, 31(10), 1900-1911.
• [22] Optovue, Inc. (2016). RTVue XR 100 Avanti System. User manual. Software Version 2016.0.0.
• [23] Lam, L., Lee, S.W., Suen, C.Y. (1992). Thinning Methodologies-A Comprehensive Survey. IEEE Transactions Pattern Analysis Machine Intelligence, 14(9), 869-885.
• [24] Hubbard, L.D., Brothers, R.J., King, W.N., Clegg, L.X., Klein, R., et. al. (1999). Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the Atherosclerosis Risk in Communities Study. Ophthalmology, 106, 2269-2280.
• [25] Xu, X., Ding, W., Wang, X., Cao, R., Zhang, M., al. et. (2016). Smartphone-Based Accurate Analysis of Retinal Vasculature towards Point-of-Care Diagnostics. Nature, Scientific Reports, 6(34603).
• [26] Cheung, C.Y., Tay, W.T., Mitchell, P., Wang, J.J., Hsu, W., et. al. (2011). Quantitative and qualitative retinal microvascular characteristics and blood pressure. Journal Hypertension, 29, 1380-1391.
• [27] Altman, D.G., Bland, J.M. (1994). Diagnostic tests. 1: Sensitivity and specificity. BMJ British Medical Journal, 308(6943), 1552.

Uwagi

EN

1. This work was supported by the Faculty of Computing, Poznan University of Technology within the Project MODRE Number 09/93/DSMK/1901.

PL

2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).